目前的NEXRAD无法可靠地实现恶劣天气下的安全飞行

W. Knecht
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引用次数: 4

摘要

摘要:目的:我们希望评估当前一代座舱内环路下一代雷达(NEXRAD)是否能够可靠地实现在严重(“重”)对流天气下的安全飞行。背景:大量研究表明,估计恶劣天气下的最近进近点(CPA)是困难的,目前的驾驶舱内NEXRAD可能本质上不适合这项任务。方法:从理论上研究,我们首先检查了在循环NEXRAD中存在的视觉信息。这预示着固有的任务难度。接下来,为了进行实证研究,我们开发了一个“理想风暴”的数学模型,生成了一个循环的nexrad型部分任务模拟,并测试了21名通用航空(GA)飞行员,以测量天气系统深度(19和40 nm)的影响,以及以不同的关闭速率打开和关闭单元之间的缝隙(14、7、0、7、14 kt)。结果:对于测试值,天气系统深度对与恶劣天气的间隙(> - 40 dBZ反射率)没有显著影响。然而,天气运动极大地降低了安全性。此外,移动速度是否像7公里那么慢,以及缺口是打开还是关闭,似乎都无关紧要。任何天气变化都使本来就很困难的任务变得更加困难。结论:分析表明,有必要增加未来预测天气和范围环。没有这两个关键要素,注册会计师的判断显然仍然是困难的。训练对于提高成绩也是必要的,但不太可能是充分的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Current NEXRAD Cannot Reliably Enable Safe Flight Around Heavy Weather
ABSTRACT Objective: We wished to assess whether current-generation in-cockpit looping Next-Generation Radar (NEXRAD) can reliably enable safe flight around severe (“heavy”) convective weather. Background: Numerous studies suggest that estimating the closest point of approach (CPA) to heavy weather is difficult, and that current in-cockpit NEXRAD may be intrinsically inadequate for the task. Method: To investigate theoretically, we first examined the visual information present in looping NEXRAD. This predicted inherent task difficulty. Next, to investigate empirically, we developed a mathematical model of an “ideal storm,” generated a looping NEXRAD-type part-task simulation, and tested 21 general aviation (GA) pilots to measure effects of weather system depth (19 vs. 40 nm), and the opening and closing of gaps at various closure rates between cells (14, 7, 0, 7, 14 kt). Results: For the values tested, weather system depth had no significant effect on clearance from heavy weather (>40 dBZ reflectivity). However, weather movement greatly degraded safety. Moreover, it did not seem to matter if movement was as slow as 7 kt, nor whether gaps were opening or closing. Any weather movement made an already difficult task more so. Conclusion: Analysis suggests the necessity of adding future-predicted weather plus a range ring. Without these two key elements, judgment of CPA will clearly remain difficult. Training is also necessary to improve performance, but is unlikely to be sufficient.
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